Instructions to use hf-internal-testing/tiny-random-levit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-levit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-levit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-levit") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-levit") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 557bbff16677e83da5dc997b3cf6d88c4cc7ac8031a562daf194e86ea379e829
- Size of remote file:
- 2.85 MB
- SHA256:
- c7f25db703ea8ea8b69b64b2cd30d32e2f0b1b3214ff557bff596e6c37ca327c
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